You are here: Home » Publications

My recent Publications (link)

Publications page of my Faculty

My citations at Google Scholar

Copyright IEEE
Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.


Leonowicz Z.: "Parametric methods for time-frequency analysis of electric signals" preprint download, published by Wroclaw University of Technology, 2006.
The author presents a new approach to spectral analysis of electric signals and related problems encountered in power systems. This approach includes the use of high- resolution subspace spectrum estimation methods (such as MUSIC and ESPRIT) as replacement of widely used Fourier Transform-based techniques. The author proves that such approach can offer substantial advantages in parameter estimation accuracy, classification accuracy and many other aspects of power system analysis, especially when analyzing non- stationary waveforms. The problems treated in this work include theoretical analysis of the limitations of FFT-based analysis, problems in applications of Short Time Fourier Transform, description and characteristic properties of subspace frequency estimation methods - MUSIC and ESPRIT; estimation of the model order, theoretical development of time-varying spectrum, application of filter banks and advantages when applying to line spectra analysis, space-phasor for analysis of three-phase signals, power quality assessment using indices with practical application to waveforms from an arc furnace power supply, numerical analysis of performance of investigated methods and a novel approach to classification of power system events based on time-frequency representation and selection of "areas of interest" in time-frequency plane. The author concludes that the use of high-resolution methods significantly improves the accuracy of many parameter estimation techniques applied to power system analysis.